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of therapeutic relevance to pancreatic cancer. Your qualifications should include: Ph.D. in Bioinformatics, Genetics, Genomics, or an equivalent field. Experience with common experimental techniques in molecular
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data Contribute to study design, data interpretation, and dissemination of findings in high-impact peer-reviewed journals and present at conferences Required Qualifications: Ph.D. in Bioinformatics
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in insect identification, insect rearing, behavior, and genetic and microbiological techniques, as well as fundamentals of statistics and bioinformatics. You will also have opportunities to develop
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skills: Experience with agricultural plant sciences, plant genetic resources, row-crop agriculture, plant genetics, plant breeding, molecular biology, bioinformatics, and data management. Ability to curate
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Stephen & Denise Adams Center for Parkinson's Disease at Yale School of Medicine | New Haven, Connecticut | United States | about 2 months ago
to therapeutic discovery You bring PhD in computer science, bioinformatics, computer science, or related field Strong coding skills (Python required; ML frameworks preferred) First-author publication(s) Experience
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are seeking a highly motivated individual to join this exciting collaborative research program that builds upon existing strengths in ADRD biology and genetics (JAX) and bioinformatics methods and machine
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workflow, including library preparation, Illumina/MinIon sequencing, bioinformatics analysis, and pathogen identification approaches. Learn to evaluate, analyze, and interpret NGS data using appropriate
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, Biostatistics, Genetics, Bioinformatics, Computer Science, Mathematics, Data Science, or a related quantitative discipline. Strong quantitative, computational, and programming skills. Excellent written and verbal
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. Training activities will include analyzing existing datasets and generating new molecular and metabolic data using advanced sequencing technologies and bioinformatics methods. Throughout the project, you
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perform bioinformatic data analysis on proteogenomic data generated across high-throughput profiling platforms from multiple cancer types. 2) Establish a comprehensive clinico-genomic database, web resource